Results 71 to 80 of about 34,984 (114)

Wind speed prediction in some major cities in Africa using Linear Regression and Random Forest algorithms

Journal of Nigerian Society of Physical Sciences
Globally, wind energy if properly harnessed, could serve as a source of energy generation in Africa. This study compared the performance of two Machine Learning (ML) algorithms (Linear regression and Random Forest) in predicting wind speed in five major
Timothy Kayode Samson, Francis Olatunbosun Aweda   +1 more
doaj   +1 more source

Consistance de la minimisation du risque empirique pour l'optimisation de l'erreur relative moyenne

, 2015
National audienceWe study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models.
de Myttenaere, Arnaud, Le Grand, Bénédicte, Rossi, Fabrice   +2 more
core  

Medium-Term Load Forecasting Of Covenant University Using The Regression Analysis Methods [PDF]

, 2014
Electric load forecasting is principal to the economic and efficient provision of electric power to meet various load demands for a specified period of time. The focus of this paper is on the medium-term load forecast of Covenant University, a Nigerian
Adewale, Adeyinka A., Awelewa, A. A., Chihurumanya, Felly-Njoku, Samuel, I. A.   +3 more
core   +2 more sources

Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards

Buildings
As the distribution of indoor contaminants is often heterogeneous, the traditional Wells–Riley equation is inadequate for accurately assessing the infection risk to indoor personnel.
Chonggang Zhou, Yunfei Ding
doaj   +1 more source

Evaluating The Accuracy of Gridded Climate Datasets for Precipitation, Surface Air Temperature, and Sea Surface Temperature in Central Java, Indonesia

Indonesian Journal of Applied Physics
Studies of climate information that rely on accurate and reliable data are essential in hydrometeorological monitoring, early warning, and climate change impacts in areas with varied topography and limited observation data, such as Central Java ...
Iis Widya Harmoko, Muhammad Zainuri, Anindya Wirasatriya, Supari Supari   +3 more
doaj   +1 more source

Wavelet-based short-term load forecasting using optimized anfis [PDF]

, 2016
This paper focuses on forecasting electric load consumption using optimized Adaptive Neuro-Fuzzy inference System (ANFIS). It employs the use of Particle Swarm Optimization (PSO) to optimize ANFIS, with aim of improving its speed and accuracy.
Abubakar, I., Khalid, S. N., Mustafa, M. W., Mustapha, M.   +3 more
core  

Comparison Airport Traffic Prediction Performance Using BiGRU and CNN-BiGRU Models

JOIN: Jurnal Online Informatika
COVID-19 pandemic has significantly disrupted the aviation industry, highlighting the critical need for accurate airport traffic predictions. This study compares the performance of BiGRU and CNN-BiGRU models to enhance airport traffic forecasting ...
Willy Riyadi, Jasmir, Xaverius Sika
doaj   +1 more source

COMPARISON OF ARIMA, LSTM, AND GRU MODELS FOR FORECASTING SALES OF HIT AEROSOL PRODUCTS

Pilar Nusa Mandiri
A more accurate forecasting model, such as LSTM, can significantly enhance business efficiency by providing more reliable predictions of future sales, allowing for better inventory management, optimized production schedules, and more precise distribution
Nendi Sunendar, Yan Rianto
doaj   +1 more source

Analisis Peramalan Permintaan Produk Indomie Di PT Indofood CBP Sukses Makmur TBK Divisi Noodle [PDF]

, 2019
PT Indofood CBP Sukses Makmur Tbk Division Noodle, there are many kinds of instant noodle products produced by one of them is Indomie. Indomie products are divided into many types of indomie products.
Setiadi, Aprilianto
core  

Volatility Modelling Using Hybrid Autoregressive Conditional Heteroskedasticity (ARCH) - Support Vector Regression (SVR) [PDF]

, 2015
High fluctuations in stock returns is one problem that is considered by the investors. Therefore we need a model that is able to predict accurately the volatility of stock returns.
Hoyyi, Abdul, Tarno, Tarno, Yasin, Hasbi
core   +3 more sources